In clinical research, such as pharmaceutical research, medical device research, psychology research, or any other human-based study or research, patients are often required to be present for multiple office visits. Some of these visits to an office or research location may entail being administered a drug or a placebo. Other visits may be a follow-up session or appointment where the patient's vital signs (e.g., blood pressure, weight, temperature, etc.) or other indicia (e.g., white blood cell count, eye dilation, etc.) may be taken and recorded.
Often, during such studies, the return visits are scheduled for a certain number of days, weeks, or months from the initial treatment day. For example, if an experimental drug was administered on day “0,” the patient may be required to return for follow-up visits at days 7, 14, 21 or on months 3, 6, and 9, and so forth. Scheduling and staffing these follow-up visits can cause many challenges.
For example, research sites often run more than one study at a time. To schedule multiple return visits for multiple studies can be a daunting task. First, different parameters need to be measured for different studies and protocols. One study may require blood testing, which means one set of supplies and staff with a certain expertise are needed, while another study may require an x-ray and an oral exam, requiring another set of supplies and staff with a different expertise. If these return visits are scheduled relative to the first visit (which fall on different days for different patients), return visits will also fall on different days, and research sites must be prepared and trained to conduct these return visits on many different occasions. This can be expensive and difficult to manage, and often deters smaller facilities from taking on multiple studies. Second, follow-up visits may require the presence of specialized staff or equipment, which means that these resources need to be dispatched to various sites on a very frequent basis. If these return visits are scheduled relative to a patient's first visit (which fall on different days for different patients), personnel and supplies are constantly being shuttled from location to location. This adds to the cost of conducting studies, because the resources needed to manage a research site are not controlled. It also means that the needs of a research site cannot be easily anticipated. The administrative challenges that are already inherent in conducting research are multiplied. However, it is often to a research company's advantage to keep the research site burden as low as possible. When this burden is lowered, data collection is easier, which can help improve the quality of data. For example, there will likely be fewer follow up queries, which many happen when a researcher sees one patient for one study and collects one type of data, and immediately afterward, sees another patient from a separate study and needs to collect a completely different set of data. In this example, the researcher may forget to take the blood pressure of the second patient in the second study because blood pressure was not required to be taken from the first patient in the first study. This “break” in flow can cause mistakes and difficulties. Third, longer studies often experience a high patient drop-out rate. Patients may begin to tire of the appointments or feel like they are participating in the study all alone, and decide to drop out. This causes multiple problems in the collecting of data, because long-term data may be unavailable. Additionally, the FDA and other organizations may imply that an adverse event occurred if follow-up data is not available for a particular patient, even though the patient may be doing well or has even improved, but simply failed to return for collection of follow-up data.
Consider the following example. If a patient in a study is required to return for a follow-up visit every three months for a year, currently, he or she would be told to call the research site or facility at about the 2½ month mark to schedule the next appointment. The patient may forget to call, which requires staff to actively conduct follow-up contact. In any event, there needs to be a receptionist or scheduler on-hand to make each appointment. If a site is working with a large number of patients on a study (e.g., with 10, 50, or 100 patients), the research site may need to coordinate 40, 200, or even 400 individual follow-up visits distributed randomly over the course of a year. Moreover, the patients are likely to all schedule on different days, which means that specific supplies need to be set out multiple times, detailed protocols may need to be re-reviewed before each follow-up day, and specialty staff may spend unnecessary time traveling to different sites throughout the week or month. In this example, if there are 10 patients in this study, and each requires 4 follow-up visits, and there is one scheduling contact and one appointment contact for each visit, there would be over 80 patient contacts. This is time-consuming and may likely lead to higher costs and inefficiencies.
Accordingly, there is a need for a system and method for scheduling patients in an organized and uniform way, preferably using a batch follow-up system. There is a further need for a system and method to improve patient retention. There is a further need to reduce scheduling costs and patient scheduling contacts.